Projection of images from an image projector typically uses a static setup wherein the image projector projects the image on a screen that is flat and arranged perpendicularly to the axis from the image projector to the center of the screen. The image projector comprises a focus lens such that the image is sharp and in focus at a given plane at a given distance from the image projector. The plane at which the projected image is in focus is known as the image plane. In a traditional system, the focus is set such that the image plane coincides with the plane of the screen. Such a focusing of the image is typically performed manually and results in a sharp image being presented.
However, whereas such a conventional system works well in many scenarios, it also has a number of disadvantages that make it less advantageous for some applications. For example, the approach requires a planar screen perpendicular to the axis between the image projector and the screen and is less suitable to a system wherein the image is projected on a non-planar surface.
For example, FIG. 1 illustrates an example wherein an image is projected by a projector 101 on a non-planar projection surface 103. As illustrated, the projector 101 may be adjusted such that the image plane 105 coincides with the projection surface 103 at some points but it is not possible for the image plane 105 to coincide with the surface 103 as such, i.e. at all points. Thus, the actual projection surface 103 will deviate from the image plane 105 and accordingly the projected image will not be in focus but will appear to not be sharp except for the specific areas where the surface 103 coincides with the image plane 105. Thus, the projected image(s) appear sharp only on the part of the surface 103 coinciding with the image plane 105. On other parts of the surface 103 (those deviating from the image plane 105), the image appears blurred due to de-focus. As a result, a substantial loss in perceived sharpness of the image may be perceived by a viewer.
In order to address such problems, one can measure the surface geometry and to design an appropriate lens that can compensate for the surface variations. However this approach is possible only with a small class of surface shapes, it is expensive and it limits the application of the projector to a specific installation/surface. In order to address the latter problem, one can use an adaptive optical system which automatically adjusts the lens system to the surface geometry. However, such adaptive optical systems are extremely expensive and are accordingly used in satellite applications but are not appropriate for e.g. consumer products.
As another example, traditional systems tend to have disadvantages when images are projected on a moving target, i.e. when the projection surface is moving. FIG. 2 illustrates an example wherein a projector 201 projects an image on a moving surface 203 which is moving along the image plane 203. However, although the surface 203 coincides with the image plane, the movement of the surface 203 results in a motion blur which may be clearly noticeable by a viewer.
If the motion of the projection surface 105 is fully known and limited to a simple translation along the image plane, the motion blur may be compensated by the projector tracking the moving surface. Furthermore, if the motion of the target is fully known, the motion blur may potentially be compensated by a pre-filtering of the image prior to projection. The pre-filter can be determined from the motion. However, in many scenarios the movement is not known or is too complex for practical tracking or compensation. Furthermore, pre-filtering tends to lead to image distortions since the motion blur tends to be characterized by zeroes in the frequency response which cannot be compensated for by a practically implementable filter.
As yet another example, chromatic, spherical or astigmatic aberrations may tend to result in reduced sharpness. For example, as illustrated in FIG. 3, chromatic aberrations can result in slightly different image planes for the different colours thereby resulting in a de-focus and thus a less sharp image for at least one of the colours. Similarly, as shown in FIG. 4, spherical aberrations may result in a smearing of the focal point along the optical axis of the lens thereby resulting in a de-focus. The astigmatic lens aberrations can give a slightly curved image plane, as illustrated in FIG. 5. If the image is projected on the flat surface this may result in a partial image de-focus.
Hence, an improved image projection approach would be advantageous and in particular an approach allowing increased flexibility, improved perceived image sharpness, reduced complexity, facilitated implementation and/or improved performance would be advantageous.